Autonomous search in a social and ubiquitous Web

Recent W3C recommendations for the Web of Things (WoT) and the Social Web are turning hypermedia into a homogeneous information fabric that interconnects heterogeneous resources: devices, people, information resources, abstract concepts, etc. The integration of multi-agent systems with such hypermedia environments now provides a means to distribute autonomous behavior in worldwide pervasive systems. A central problem then is to enable autonomous agents to discover heterogeneous resources in worldwide and dynamic hypermedia environments. This is a problem in particular in WoT environments that rely on open standards and evolve rapidly—thus requiring agents to adapt their behavior at run time in pursuit of their design objectives. To this end, we developed a hypermedia search engine for the WoT that allows autonomous agents to perform approximate search queries in order to retrieve relevant resources in their environment in (weak) real time . The search engine crawls dynamic WoT environments to discover and index device metadata described with the W3C WoT Thing Description, and exposes a SPARQL endpoint that agents can use for approximate search. To demonstrate the feasibility of our approach, we implemented a prototype application for the maintenance of industrial robots in worldwide manufacturing systems. The prototype demonstrates that our semantic hypermedia search engine enhances the flexibility and agility of autonomous agents in a social and ubiquitous Web.